Artificial Intelligence & Its Role In Branding & Marketing

By harnessing the power of artificial intelligence marketing tools, marketers can streamline their workflows and free up quite a bit of time for strategic initiatives, writes Niranjan Gidwani

We can confidently say that the rise of artificial intelligence (AI) has revolutionised the world of branding. AI, including advanced systems like ChatGPT and Bard, has emerged as a game-changer in the world of marketing and advertising and has significantly revolutionised the way businesses approach marketing strategy. In fact, without having spent any money on promoting the brand, ChatGPT has become a global brand in a short span of a few months, just going viral.

By harnessing the power of artificial intelligence marketing tools, marketers can streamline their workflows and free up quite a bit of time for strategic initiatives, thanks to the automation of mundane, routine tasks.

What are the most significant advantages of using AI branding and marketing?

  • One of the most significant advantages is the ability to analyse vast amounts of data quickly and accurately. By doing so, AI provides valuable insights into consumer behaviour, preferences, and purchase patterns. This in turn helps brand managers to make extremely informed decisions about product development, placement, pricing and marketing strategies.
  • AI also monitors social media platforms and all online forums. It provides feedback in real-time and on-the-go on consumer opinions and sentiments towards brands.
  • AI assists brand experts in optimising their branding strategies. By analysing data on consumer engagement with branding materials, AI provides insights on what types of content perform best, and which channels are most effective in reaching the target audience. This helps in improving overall brand performance.
  • AI has the ability to create personalised marketing campaigns. AI algorithms analyse data on consumer preferences and behaviour. There are major banks, brands, retailers and online players using AI-powered chatbots. These engage with customers in real time, providing personalised recommendations and assistance based on their purchase history and preferences.
  • Although there is an initial investment cost, the utilisation of AI marketing tools has surely led to significant cost savings for marketing agencies. These tools offer automation and efficiency, reducing the need for manual labour and streamlining various marketing processes.

What are the risk factors?

  • Data protection - AI marketing tools rely heavily on data collection and analysis. The handling of sensitive customer data raises concerns about privacy and security. It is crucial for businesses to ensure robust data protection measures and comply with relevant regulations which are only increasing.
  • Bias factor - AI algorithms are trained on historical data. Historical data would mean GIGO – Garbage in, Garbage out. This may contain inherent biases. These biases can inadvertently influence decision-making processes, leading to unfair or discriminatory outcomes. The bias factor would definitely need to be mitigated.
  • Lack of human judgment - Overreliance on AI without human oversight can result in incorrect or inappropriate responses, negatively impacting customer experiences and brand reputation. Therefore, the mix of technology and personal decision-making intervention is a must.
  • Technology reliability and dependability - AI marketing tools are reliant on technology infrastructure and may be susceptible to technical glitches, system failures, or limitations. Overdependence on AI without contingency plans can disrupt marketing operations and impact customer experiences if issues arise.
  • Risk Mitigation - To mitigate these risks, businesses should implement proper governance frameworks, conduct regular audits, and maintain transparency and explainability of all algorithms to company owners and heads.

There are far too many brands that fail to develop deeper relationships with consumers, they are content to make the occasional transaction every now and then. They believe that the best technology or the best product wins. But it often doesn’t. They lack a clear understanding of how to build a brand – how to build from strength – and underestimate the impact that brand loyalty and brand advocacy have on the cost of customer acquisition.

The level of trust in a brand determines its ceiling – its potential. Trusted brands get bought, used, and recommended more. They eventually end up with a higher proportion of loyal customers and are more profitable.

But as important as trust is, relevance is essential for developing deeper relationships with consumers. A high level of trust that does not translate into greater relevance is unfulfilled potential of the brand and its business.

Cadbury India and Bollywood star Shahrukh Khan are redefining the world of advertising. An innovative campaign is in partnership with Indian AI startup Rephrase AI, a pioneer in synthetic media. The company has harnessed generative AI and machine learning to craft hyper-targeted content, giving local shops personalised ads with Khan’s likeness at zero cost, opening the door to a new era of personalised, large-scale communication.

Now that we know the significant strengths of AI in building brands and marketing, now that we have seen some of the risks that need to be mitigated, the last and the most important aspect, in my personal view, in this entire region, is a certain reluctance or lack of desire to be data-driven in terms of decision-making.

There is still a lot of the old-school approach which is to seek informal information from few market sources and make decisions.

We just have to see the example of the Government machinery of the UAE. This has become completely data-driven. The Indian government is rapidly following suit.

UAE is probably the only place in the world where the Government is much ahead of the curve while the private sector continuously plays “catch up”.

The top 10 per cent of private and public sector companies are probably the only ones which have transitioned to real database decision-making.

The lowest 30 per cent may still take a long time.

It’s the middle 60 per cent, the backbone of the economy, who need to eliminate the reluctance to invest in technology, upgrades and artificial intelligence-based, data-based decision-making.

(Niranjan Gidwani is a Consultant Director | Member of UAE Superbrands Council | HBR Advisory Council | Charter Member Tie Dubai)

Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house. Unless otherwise noted, the author is writing in his/her personal capacity. They are not intended and should not be thought to represent official ideas, attitudes, or policies of any agency or institution.